Several studies have been done previously, analyzing the shapes and appearances of cell nuclei in cytological (biopsy) samples using machine-vision and -learning techniques. Much less work has focused on histological micrographs, likely because their analysis is considerably more difficult, and up to now, no automated system exists for this type of analysis.
In histological micrographs the appearances of the tissue and of the cell nuclei may change substantially from one sample to the next due to variations in staining, aging of the sample, or due to artifacts introduced during sample preparation. Often it is difficult to delineate clearly the chromatin from the surrounding cell plasma or the stroma. Moreover, an automated scanning system usually records images only at one focal position, and at higher magnifications not the whole depth of the sample is in focus. Pathologists tend to scan the plane of focus up and down through the sample when inspecting nuclei at a high magnification. Additional difficulties arise since the tissue may have been damaged by the excise instruments or during sample preparation, resulting in areas that cannot be used for an analysis at all.
All these factors contribute to an increase in complexity of the analysis. Accordingly, a method and system for nuclear analysis of biopsy images is needed that substantially overcomes the above-described problems.